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Overview: The need for effective behavioral interventions has never been greater, but existing interventions yield weak and/or difficult to replicate effects. Further, implementation of behavioral interventions at scale is rare, and may further dilute intervention effects. The NIH Stage Model provides a framework for guiding intervention development from early phase discovery through large scale implementation, and the NIH Science of Behavior Change (SOBC) program has articulated a rigorous method for incorporating the underlying mechanisms of behavior change at each stage of intervention development. This talk will discuss how the two frameworks for research complement each other, and how individual researchers can adopt practices that will yield more powerful, replicable, and informative interventions.

Various resources are publically available for those in the research community looking for funding opportunities and research materials related to COVID-19. In an effort to collect those resources for COVID-19 research, the following links are made available here and on the SOBC Resources page.

1. The NIH Office of Behavioral and Social Sciences Research’s (OBSSR) collection of funding opportunities specific to COVID-19 and the Behavioral and Social Sciences. Link here.

2. NIH Public Health Emergency and Disaster Research Response (DR2). NIH DR2 provides various data collection tools, resources, and training materials for public health emergencies and disasters, including the current COVID-19 pandemic. Link here.

This presentation describes mediation analysis and the connections between traditional mediation analysis and recently developed causal mediation analysis. Mediating variables have a long and important history in theoretical and applied research because they describe how and why two variables are related. One common example of applied mediation research is the study of the mediating processes that explain how a prevention/treatment program achieves its effects on an outcome variable. If the intervention’s active ingredients are identified, the intervention can be made more powerful and more efficient. Other applied mediation examples include identifying how a risk factor leads to disease and how early life experiences affect later development.

Important recent developments in causal mediation analysis include new counterfactual (potential outcomes) methods that generate accurate estimates for continuous and categorical measures. In general, researchers have been slow to adopt causal mediation methods because of their complexity and the perceived lack of connection between traditional and causal methods. However, understanding connections between traditional and causal mediation increases understanding of both methods. The background for each approach is described, along with questions about traditional mediation and potential outcomes that causal mediation perspectives can help answer. The presentation ends with future directions in mediation theory and statistical analysis.

The Office of Strategic Coordination (OSC), which manages the Common Fund, is issuing this Notice of Special Interest (NOSI) to stimulate innovative research on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the disease it causes, Coronavirus Disease 2019 (COVID-19). OSC seeks new, innovative perspectives and approaches to the prevention of, preparation for, or response to coronavirus SARS-CoV-2, domestically or internationally. The funding for this supplement is provided from the Coronavirus Aid, Relief, and Economic Security (CARES) Act, 2020.

OSC is therefore offering Emergency Competitive Revisions to active Common Fund grants and cooperative agreements addressing the research objectives described below.

Dr. Kevin Volpp is the Founders Presidential Distinguished Professor at the School of Medicine and the Wharton School at the University of Pennsylvania and the Director of the Penn Roybal Center for Health Incentives and Behavioral Economics (CHIBE), 1 of 2 original NIH-funded Centers in Behavioral Economics and health. He is also the Division Chief of Health Policy for the Department of Medical Ethics and Health Policy and a special advisor to the CEO of Penn Medicine and the Dean/EVP. He is known nationally and internationally for developing the application of behavioral economics to health and for designing and testing initiatives to improve health that have been implemented in tens of millions of Americans. He has garnered numerous awards for his research including election into the National Academy of Medicine, the British Medical Journal Group Award for Translating Research into Practice, and Article of the Year and Career Achievement Awards from multiple societies, including from NIH for work in social and behavioral sciences and the John Eisenberg Award from the Society of General Internal Medicine. He served on the Editorial Board of the Annals of Internal Medicine and as a Contributing Writer to JAMA and is now on the Editorial Board of the NEJM Catalyst.

The NIH Office of Behavioral and Social Sciences Research (OBSSR) is seeking broad public input on important new directions for health-related behavioral and social sciences research (BSSR). Specifically, OBSSR requests your input on research directions (see RFI): that will support the achievement of the scientific priorities in the OBSSR Strategic Plan 2022-2026 (see current strategic plan) and that will advance or transform the broader health impact of BSSR. OBSSR is interested in focusing on research directions that are trans-disease and cross-cutting in nature and address critical gaps in the field.

The National Institute on Aging-funded Stress Measurement Network, in collaboration with Gateway to Global Aging Data (see g2aging.org), produced by the Program on Global Aging, Health & Policy, University of Southern California, has recently completed the harmonization of psychosocial stress variables across nine longitudinal studies on aging from around the world.

These newly harmonized psychosocial stress measures allow researchers to compare and contrast relationships between stress constructs (e.g., exposures, responses, buffers) with health and aging outcomes, within and across different geographic and cultural contexts. The data are free to the public as part of the Health and Retirement Study family of studies and include data from the US, Europe, Korea, Japan, China, Mexico, and Costa Rica. The stress types that have been harmonized across each wave of these studies are stressful life events, traumatic events, chronic stress, childhood adversity, discrimination, loneliness, social isolation, relationship strain, work stress, and neighborhood safety.

To foster the utilization of this rich resource, the Stress Measurement Network will support five exemplar projects that examine cross-national relationships between stress and aging with mentorship from senior faculty, priority access to the harmonized data and the lead data programmer, statistical consulting, and a $2,500 honorarium.

M.A. “Tonette” Krousel-Wood MD, MSPH, FACPM, FAHA is Professor of Medicine in the Tulane School of Medicine, Professor of Epidemiology in the Tulane School of Public Health and Tropical Medicine, and serves in several leadership roles at Tulane including the Associate Provost for the Health Sciences at Tulane University. She is actively engaged as the principal and co-investigator in NIH-funded clinical research and clinical trials focused on overall and sex differences in adherence to prescribed therapies for chronic diseases, management of hypertension, and health outcomes and implementations research focused on women and men with chronic cardiometabolic diseases in rural and underserved areas.

Recent advances in the design and evaluation of behavioral and biobehavioral interventions include the Multiphase Optimization Strategy (MOST) and the Behaviour Change Intervention Ontology (BCIO). Inspired by engineering, MOST is a framework for development, optimization, and evaluation of behavioral interventions, where optimization is defined as the process of identifying the intervention that provides the highest expected level of effectiveness obtainable within key constraints imposed by the need for efficiency, economy, and/or scalability. Part of the Human Behaviour Change Project, the BCIO is a set of definitions for entities and relationships used to describe behaviour change interventions, their contexts, effects and evaluations. Development of the BCIO is ongoing and has involved a combination of reviewing, refining and extending existing relevant ontologies and taxonomies (such as the Behaviour Change Techniques Taxonomy (BCTTv1)), consultation with ontology experts, and peer review from, and discussions with, international behaviour change experts. In this webinar, Dr. Linda Collins, a developer of MOST, and Dr. Susan Michie, a lead investigator for the Human Behaviour Change Project and BCIO, will outline the ways in which elements of BCIO complement the MOST framework and how behavioural scientists can incorporate principles from both frameworks/ontologies into their work.

Roughly a third of all adults in the United States have high blood pressure, a major risk factor for heart disease and stroke. It’s a condition that can be largely controlled with diet, exercise and medication, yet the Centers for Disease Control and Prevention estimates that only about half of the 75 million people who have high blood pressure manage to keep it in check. In November, Eric Loucks, director of the Mindfulness Center at the Brown University School of Public Health, and colleagues published a study in Plos One, a science journal, that put forward a possible solution: an eight-week mindfulness-based program.